Autisic Disorder (AD) is a severe neuro-developmental disorder characterized by marked social and language abnormalities and by sterotypic repetitive behavior. The etiology of AD is unknown, but it is believed to be strongly influenced by genetic factors. The goal of this new project is to identify all genes with major to moderate effectso n the risk of autistic disorder. The investigators propose to achieve this goal through six specific aims. 1) To ascertain and sample 200 multiplex AD families as well as 200- 250 sporadic AD patients and their parents between the two study centers at Duke University and the University of South Carolina. Strict diagnostic criteria will be used based on validated diagnostic instruments. 2) Perform a 10 cM genomic screen using a multi-tiered approach for replication and follow up of interesting regions and state-of-the-art statistical genetic analysis. Both model-based and model -ree methods of anlaysis will be used. Initial screening will be based on 100 families in order to identify regions warranting follow-up. 3) Follow-up regions of interest identified by the initial genomic screen. Criteria for follow-up will include a p-value less than about 0.01 for model free analysis and/or its equivalent of a lod score greater than 1. Follow-up will include genotyping of the second tier of 100 multiplex familes for the original marker and two new flanking markers in the entire data set. 4) Genotype very interesting regions that reach a p-value level <0.0001 and/or lod score of >3.00 with all know polymorphic markers in the region to permit both linkage analysis and family-based association studies to detect any linkage disequilibrium. 5) Examine potential candidate genes. If the screen and follow-up identify one or more small regions, genes in those regions will be examined. Candidate genes or linkages identified or suggested by other researchers also will be followed up. Analyses will include linkage and association/disequilibrium analyses. 6) Characterize Japanese and Finnish families provided by collaborators. These data sets have the advantage of being relatively homogeneous and can be used to confirm the generality of a major effect as well as in fine mapping.